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Recent Patents on Mechanical Engineering - Online First
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Performance Analysis of IoT-based Temperature Monitoring Box Type Solar Cooker: A Multi-objective Optimization Approach
Available online: 30 December 2024More LessBackgroundThe idea behind the Internet of Things is to bring the virtual world into the physical one by connecting commonplace items. With the help of the Internet of Things (IoT), it is possible to remotely sense or control objects through preexisting network infrastructure. This opens up possibilities for computer-based systems to integrate with the physical world, which in turn improves efficiency, accuracy, and economic benefit while reducing the need for human intervention.
ObjectiveThe purpose of this patent study is to investigate how a (NSGA-II) multi-objective genetic algorithm might be utilized to optimize the execution of an Internet of Things (IoT) temperature monitoring Box-Type Solar Cooker (BTSC). To determine the best set of output parameters for an IoT temperature monitoring box-type solar cooker, (NSGA-II) multi-objective genetic algorithms are used to perform optimizations of the figure of merits (F2), cooking power, cooker efficiency, and final water temperature.
MethodsThe present research work involves the development of a Wi-Fi module system integrated with a smart temperature monitoring system for a BTSC. Keeping track of the temperature data from different locations in the BTSC through the IoT system was the primary objective of this project. A waterproof temperature sensor (DS18B20) was used to keep monitoring. After that, the data was shown on an LCD, stored on a microSD card, and made available through a smartphone. The Blynk Applications' IoT was employed. Using existing data, regression-based computational models are developed to describe the complex correlations between the decision-processing parameters and the input parameters of an IOT-based solar cooker. These models are applied in the objective functions after determining that a genetic algorithm is more appropriate for the problem. To forecast the optimal values about the figure of merits (F2), cooking power, cooker efficiency, and final water temperature, the Pareto fronts have been developed.
ResultsWe compare the values of response variables that were gathered experimentally with the values that were predicted by NSGA-II. The predicted values are found to be quite close to experimental values. This indicates that the multi-objective optimization method, as used in this study, has very good prediction performance. The test results are graphically shown using the error bar. Therefore, it is clear that the optimization process used to adjust the parameters of the solar cooker's performance has been quite effective. According to the findings of the experiment, the temperature at which a cooking pot remained stagnant on average was 158°C. It was determined that the cooker was of class A based on the values of the first figure of merit (F1), the second figure of merit (F2), and the cooking power (P), which were respectively 0.132, 0.359, and 86.108 W. Therefore, the thermal efficiency of the IoT-base temperature monitoring box type solar cooker is 39.99%.
ConclusionThe findings of this inquiry furthermore produced the outcome that the model provided can be applied conveniently with a confidence level of 95% to calculate the figure of merits (F2), cooking power, cooker efficiency, and final water temperature value of an Internet of Things-based temperature monitoring BTSC. The performance of IoT-based BTSC is optimized by providing real-time monitoring and data visualization, ultimately improving their efficiency and reliability. This research provides an educational tool to promote awareness and understanding of renewable energy sources and their potential benefits.
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Preparation and Characterization of Fe3O4-Modified Graphene Oxide as Heat Transfer Additive for Paraffin Wax Applications
Authors: Shuo Wang, Li Jia, Chao Dang, Honglei Ren, Zhifeng Chen, Huiming Wang and H.W. JiaAvailable online: 12 December 2024More LessIntroductionIn phase change thermal management systems, the development of magnetic phase change materials offers the possibility of effectively integrating passive and active heat control technologies..The low dispersibility of traditional heat transfer additives, the high interfacial thermal resistance with phase change matrices, and the restricted magnetic response characteristics are some of the current problems that must be resolved.
MethodTo overcome these challenges, this study employed a co-precipitation method to composite magnetic nanoparticles Fe3O4 with graphene oxide (GO). The active sites on GO were functionalized with alkyl groups to prepare Fe3O4-modified graphene oxide (Fe3O4-MGO)/paraffin magnetic composite phase change materials. The morphology, structure, chemical composition, and thermal properties of the resulting magnetic composite phase change materials were tested and characterized.
ResultThe results indicated that Fe3O4-MGO exhibits good dispersibility in paraffin, which can enhance the thermal conductivity of the phase change material. The thermal conductivity of the composite phase change material with a Fe3O4-MGO mass fraction of 2.0% was measured to be 0.461 W/m·K, representing a 47.3% increase compared to pure paraffin. Additionally, Fe3O4-MGO demonstrated a certain phase change capability, with a phase change enthalpy reaching 70.35 kJ/kg.
ConclusionThe findings of this study are expected to provide technical support for innovative applications of magnetic-controlled phase change thermal management.
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Impact of 3D Printing Settings on Polylactic Acid Filament Mechanical Behaviors Based on the Taguchi Method
Authors: Ghalia Nhassa, Romdhane Ben Khalifa and Ali SnoussiAvailable online: 12 December 2024More LessIntroduction3D printing has become an activity changer in some sectors allowing the creation of personalized parts. With its growing popularity in areas needing mechanical capabilities, it is essential to grasp how the printing settings impact the mechanical traits of the printed pieces.
MethodThis paper presents a novel investigation into the impact of critical 3D printing parameters on the mechanical characteristics of polylactic acid (PLA), a widely used biocompatible and biodegradable polymer. Our experimental approach systematically evaluated the effects of various printing parameters including infill density, raster orientation, outline overlap, and print speed on the printed parts' tensile strength and Young's modulus.
ResultThe results consistently showed that increasing the infill density and outline overlap improved tensile strength and Young's modulus. However, higher print speeds decreased both underscoring the practical application of our unique findings. This research is a pioneering effort providing engineers and designers with valuable direction for working with 3D-printed PLA parts in aerospace, automotive, and biomedical applications.
ConclusionIt significantly adds to the expanding corpus of research on the connection between 3D printing process variables and the mechanical characteristics of advanced polymeric materials.
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Computational Fluid Dynamics Analysis and Optimization of a Double-suction Turbine Agitator
Authors: Zhong Chen, Zuxiao Song, Rui Peng and Guohui MaAvailable online: 07 November 2024More LessBackgroundAs one of the essential pieces of chemical equipment, a reactor provides the necessary reaction space and conditions for the materials involved in the reaction during the stirring process. However, under typical operating conditions, issues such as uneven gas distribution, suboptimal gas-liquid mixing, and low product yield often arise in gas-liquid phase reactors.
PurposeTo address the issues prevalent in current stirred reactors, a new design for a stirred reactor equipped with a double-suction turbine agitator was developed.
MethodIn this paper, a stirred reactor equipped with a double-suction turbine agitator was designed, and its three-dimensional modeling was conducted using SolidWorks. Computational Fluid Dynamics (CFD) simulations, based on the Euler-Euler two-phase approach with the RNG k − ε turbulence model, were performed to assess variables such as stirring speed, installation height, blade diameter and agitator inner diameter. The dispersion characteristics and flow field behaviors of the gas-liquid two-phase under varying conditions were comparatively analyzed. Optimizations were conducted across various parameters to enhance the gas mixing efficiency in the liquid phase.
ResultThe results show that a diameter of 370mm for the double-suction turbine agitator, an installation height of 640mm, a blade diameter of 500mm, and an inner hole diameter of 200mm yield optimal gas-liquid two-phase mixing performance. This configuration results in a broad and uniform gas distribution within the reactor, maintaining a desired high level of gas holdup at specific positions.
ConclusionThe double suction turbine agitator is a type of radial agitator. During operation, it induces significant centrifugal forces in the liquid, exerts a robust shear effect, and enhances the mixing of the gas-liquid phases, thereby increasing the production efficiency of the product.
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Research Progress on Industrial Robots: A Review
Authors: Vilas B. Shinde, Padmakar J. Pawar and Vijay S. GadakhAvailable online: 05 November 2024More LessThe success of the fourth and upcoming fifth industrial resolution lies majorly in automation and robotics. Industrial robots perform various manufacturing-related tasks due to their autonomy, flexibility, and autonomous work in a complex environment. Applications including drilling, material transfer, loading and unloading machines, processing, assembling, and inspection, welding, spray painting, machining, and so on are common. The present work comprehensively summarizes all the pertinent work related to the industrial robot, such as inverse kinematics problems, robot design, programming, scheduling, motion planning, and trajectory planning. In addition, the present work discusses various optimization algorithms employed in industrial robots. Furthermore, several recommendations for future research have been addressed.
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RSM Hybrid Modeling of a BSFC for a Single Cylinder Four Stroke CI Engine Fueled with Nano-additives Added to Diesel-biodiesel Fuel Blends
Authors: Nishant S. Thakar and Tushar M. PatelAvailable online: 25 October 2024More LessIntroductionThe expanding need for fossil fuels emphasizes the necessity to comprehend renewable energy sources.
MethodsThis study examined the performance of a single-cylinder diesel engine using Jatropha biodiesel and aluminum dioxide the research aimed to evaluate engine reactivity to compression ratio and load variations. The experiment employed with varitaion compression ratios
ResultsThis study used the Response Surface Methodology to find the best Brake Specific Fuel Consumption performance indicator location. The researchers used a Central Composite Design setup for analysis. A regression model employing the response surface approach was then created to predict fuel phase-out likelihood
ConclusionThis study examines multiple factors' effect and highlights the potential for patentable innovations in renewable fuel applications. According to studies. Jatropha biodiesel and its blends may improve engine efficiency and lower brake-specific fuel consumption compared to diesel fuel. Minor input parameter modifications are needed to gain these benefits.
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Typical Scenario Load Identification Based on Feature Fusion and Transfer Learning
Authors: Lingzhi Yi, Yuhang Gao, Yahui Wang, Bote Luo, Zhehao Huang and Jiangyong LiuAvailable online: 22 October 2024More LessBackgroundThe electricity demand is continuously increasing. However, various institutions, enterprises, and individuals exhibit many irregularities in their electricity usage, leading to significant wastage of electricity. To achieve effective energy management, researchers are attempting to analyze and regulate users' electricity demands by monitoring their load usage through Non-Intrusive Load Monitoring (NILM) technology. The accuracy of load identification in this technology will greatly impact the results of load monitoring. Although there are currently many articles and patents related to NILM, they utilize a large amount of computational resources and require high sampling rates from devices, yet the results are still unsatisfactory. Therefore, it is necessary to improve the accuracy of load identification in data with relatively low sampling frequencies.
ObjectiveTo improve the accuracy of load identification with low sampling frequency data, this paper proposes a typical scenario load identification method based on feature fusion and transfer learning.
MethodsThis method adopts the fusion of current and power factor angles to provide abundant identification information for NILM, effectively reducing the situation of single-feature overlap of different loads. By inputting the fused feature data into GoogLeNet and utilizing transfer learning for training, not only is the accuracy improved, but also the training time and the requirement for the sampling rate of training data are greatly reduced. In addition, selecting typical scenario loads can monitor loads in a targeted manner, reduce the waste of computing resources caused by irrelevant loads, and more effectively guide electricity usage strategies.
ResultsThe proposed load identification method was tested on the low sampling frequency dataset used in this paper. It achieved an overall load identification accuracy of 94.61% across three scenarios, improving accuracy by 3% to 7% compared to other models.
ConclusionThe simulation results indicate that this method achieves high load identification accuracy at low sampling frequencies. It also exhibits good generalization ability. This method not only reduces the performance requirements for monitoring equipment but also enhances monitoring efficiency.
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Combinatorial Method for Quality Improvement of the Thrust Plate – A Case Study
Authors: M Shilpa, MR Shivakumar, Hamritha S, Akhil Kumar Singh, Vikas Goyat and Rakesh Kumar PhandenAvailable online: 15 October 2024More LessAimThis research aims to mitigate defects in the turning operation of thrust plates used in fighter jet fuel tank assemblies, thereby reducing the rejection rate and improving overall quality. This aligns with the aerospace industry's reliability goals.
BackgroundThe thrust plate is a critical component in fighter jet fuel tank assembly, transmitting engine thrust to the airframe. Quality compromises in this component can impair jet performance. It was observed that the thrust plate had a rejection rate of about 2.9% due to various defects. This real-world scenario underscores the importance of our study on the thrust plate and its potential impact on the aerospace industry. The rejection rate underscores its significance and potential for patent by quality improvement in turning of the thrust plate.
ObjectiveThe objective is to mitigate turning operation defects on the thrust plate to reduce rejection rates, aligning with aerospace industry reliability goals.
MethodsExperimentation encompassed four pivotal factors: turning speed, feed rate, cutting depth, and tool inserts, implemented through Taguchi's Orthogonal Array technique. Grey Relational Analysis was utilized to optimize parameters in thrust plate turning. Specifically, this paper targeted the enhancement of its diameter, surface roughness, and tool life.
ResultsA single coefficient for the multiple responses, i.e., grey relational grade, has been determined, and optimum levels for the parameters have been identified. Confirmation experiments with the optimal factor level combination were carried out on a sample of thrust plates, and no rejections were observed.
ConclusionAn experimental design based on Taguchi’s orthogonal array approach was used to conduct the experiments. The Grey Relational Analysis has been applied to analyze the experimental results and optimize the turning operation process parameters for the responses thrust plate diameter, tool life, and surface roughness. With this, the rejection of the thrust plate has been considerably reduced.
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Experimentally Investigating the Potential of Iso-Stoichiometric GEM Blends as a Drop-in Replacement for E50 in SI Engines
Authors: Farooq Shaik and Vinay Kumar DomakondaAvailable online: 11 October 2024More LessBackgroundResearch on alternative fuels for internal combustion engines is crucial due to climate change and energy security concerns. Ethanol-blended gasoline has been a popular alternative fuel, but biomass limitations restrict its widespread use. Methanol offers a solution as it can be produced from non-food sources, extending ethanol's availability.
ObjectiveThis study explores a ternary fuel blend consisting of gasoline, ethanol, and methanol as an alternative to binary gasoline-ethanol blend. The objective is to investigate if the iso-stoichiometric ternary blend offers equivalent fuel properties to E50 (Ethanol 50%, Gasoline 50% (v/v)) gasohol while potentially enhancing engine performance, reducing emissions, and improving combustion characteristics.
MethodsA single-cylinder, four-stroke, port fuel injection spark ignition engine was used. The engine was tested with three fuels: pure gasoline, E50 blend, and an equivalent iso-stoichiometric GEM blends. Engine tests were conducted at constant load with varying engine speeds. Performance, emission, and combustion parameters were experimentally measured and compared across all fuels.
ResultsE50 and its equivalent blends improved brake thermal efficiency but increased brake specific fuel consumption compared to gasoline. It significantly reduced unburned hydrocarbon and carbon monoxide emissions but slightly increased nitrogen oxide emissions.
ConclusionFormulated E50 equivalent blends have identical air to fuel ratio, lower heating values as conventional binary E50 gasoline-ethanol blends. The study suggests that iso-stoichiometric GEM blends have the potential to be a viable alternative drop-in fuel for E50 in internal combustion engines. The future advancements in GEM blends, particularly in optimizing ratios, could lead to patentable inventions.
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Exploring Emergent Nanotechnology Applications in Mechanical and Health Engineering
Authors: Lucio Nobile and Stefano NobileAvailable online: 11 October 2024More LessNanotechnology is a promising area of research in science and technology with potential benefits in automotive, aircraft, construction, energy, healthcare, agriculture, food processing, although it has its own risks in environmental sustainability. Recent advances in this area have stimulated research and their applications in different fields, with important results in mechanical engineering and health engineering. The aim of this article is to give an overview of some recent advances of nanotechnology, exploring emerging applications of these typical technologies. Examples of some successful practical applications in mechanical and healthcare engineering based on this technology are given, and an analysis of the prospects and main problems of this area is also conducted. Furthermore, mechanical engineers and health professionals would find this review valuable in updating their knowledge on the latest developments in nanotechnology applications.
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Graphene Coating and its Effect on Performance of Box Type Solar Cooker: An Experimental Investigation
Authors: Harshita Swarnkar, Ritu Jain and Amit TiwariAvailable online: 11 October 2024More LessBackgroundSolar cookers have been the subject of several theoretical and empirical investigations, with numerous modifications attempted to increase efficiency and security. Solar cookers need much sophisticated research and enhancement work to function better. A thorough grasp of the application of graphene in box-type solar cooking systems is crucial for both solar energy and graphene.
ObjectiveTo improve the performance of box-type solar cookers, this patent research aims to offer an experimental investigation and insightful information on of applying graphene coating to the absorber plate and its derivative.
Materials and MethodsTo ensure equal dispersion of graphene into the black paint, three samples containing (1, 3, and 5wt%) of graphene embedded with the paint were produced with 1mm, 3mm, and 5mm thickness of the coating and stirred at 400 rpm for two hours using a magnetic stirrer. X-ray diffraction and scanning electron microscopy have been studied to comprehend the influence of graphene nanoparticles on the surface morphology of the coated absorber panel. Performance evaluations of the box-type solar cookers were conducted with and without a graphene coating on the absorber plate, and data has been recorded for each case.
ResultsThe results of patent research show that the absorber plate with (1, 3, and 5wt.%) of graphene embedded with black paint 1mm, 3mm, and 5mm thickness coating has a maximum thermal efficiency of 41.48% with 97.08 W cooking power, 46% with 109.35 W cooking power, and 49% with 114.77 W cooking power for the average solar irradiation is 978 W/m2.
DiscussionIt was determined that the cooking power (P), the first figure of merit (F1), and the second figure of merit (F2) were all satisfactorily achieved. Embedding black paint into graphene coating has been shown to significantly influence the heat transmission and thermal performance enhancement of box-type solar cookers, as demonstrated by the findings of X-ray diffraction and Scanning Electron Microscopy analysis.
ConclusionThe current research makes it abundantly evident that the incorporation of graphene into the absorber plate of a box-type solar cooker, together with the application of a black paint coating, leads to increased heat transfer rates, which in turn provides an increase in cooking power. Because of this, graphene is an attractive nanomaterial that has the potential to improve the performance of box-type solar cookers, which is the novelty of this research work.
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Investigation of Stress and Wear Analysis for Aluminum-based Metal Matrix Composite Reinforced Silicon Carbide using ANSYS Software Package
Authors: Shivam Tiwari, Rakesh Kumar Yadav, Naveen Kumar and Gurbhej SinghAvailable online: 11 October 2024More LessIntroductionThis research paper examines the mechanical and wear properties of aluminium-based cast composites, an exciting category of materials with many different uses. The study aspires to understand more about the effectiveness of these composites under various conditions and weights.
MethodThis investigation aims to identify the microstructural constituents that influence resistance to wear and mechanical strength. The outcomes will provide fascinating knowledge regarding possible applications of these composites in the field, notably manufacturing, aeroplanes, and shipping, whereby lightweight materials with superior strength and resistance to wear are extensively demanded. Whenever utilized, these reinforcements act like bearing structures that prevent cracks. Aluminium lacks the characteristics needed for a wide range of engineering applications.
ResultsAs a result, it is critical to produce aluminium-based alloys with all of the combinational circuitry properties required to meet our relevant requirements.SEM (scanning electron microscopy) anatomical assessments of aluminium, silicon carbide, and iron. The current inquiry examines the implications of the particle stages on the microhardness, elastic modulus, and mechanical and wear features of aluminium as the base material and silicon carbide as a reinforcement material for composites. The sample’s microhardness and modulus of elasticity improve from 64 to 70 and 688 MPa to 719 MPa, correspondingly, when the weight percentage of silicon carbide (micro %15 and nano%1, 2, 3, 4).
ConclusionThe various test results are examined in this investigation and made available for correlation with one another. The mechanical features and resistance to wear of aluminium matrix composites manufactured using several methods have been explored.
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